Precision medicine's goal is to use vast multidimensional biological datasets to build and enhance diagnosis, therapeutic intervention, and prognosis pathways that reflect individual diversity in genes, function, and environment. Artificial intelligence (AI) algorithms can currently forecast risk in some malignancies and cardiovascular diseases from available multidimensional clinical and biological data with fair accuracy due to high computer capabilities. Diabetes AI assistants have been proved to be effective in managing patient problems. As artificial intelligence (AI) becomes more prevalent in precision medicine, it can assist organizations in a variety of ways. In terms of data issues, AI employs deep learning techniques to solve the difficulties that massive data sets and unstructured data provide.